Claude-skill-registry langfuse-install-auth

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/langfuse-install-auth" ~/.claude/skills/majiayu000-claude-skill-registry-langfuse-install-auth && rm -rf "$T"
manifest: skills/data/langfuse-install-auth/SKILL.md
source content

Langfuse Install & Auth

Overview

Set up Langfuse SDK and configure authentication for LLM observability and tracing.

Prerequisites

  • Node.js 18+ or Python 3.9+
  • Package manager (npm, pnpm, or pip)
  • Langfuse account (cloud or self-hosted)
  • Public and Secret keys from Langfuse dashboard

Instructions

Step 1: Install SDK

# Node.js / TypeScript
npm install langfuse
# or
pnpm add langfuse

# Python
pip install langfuse

Step 2: Get API Keys

  1. Go to Langfuse dashboard (https://cloud.langfuse.com or your self-hosted instance)
  2. Navigate to Settings -> API Keys
  3. Create new API key pair (Public Key + Secret Key)
  4. Note your host URL (cloud:
    https://cloud.langfuse.com
    )

Step 3: Configure Authentication

# Set environment variables
export LANGFUSE_PUBLIC_KEY="pk-lf-..."
export LANGFUSE_SECRET_KEY="sk-lf-..."
export LANGFUSE_HOST="https://cloud.langfuse.com"  # or self-hosted URL

# Or create .env file
cat >> .env << 'EOF'
LANGFUSE_PUBLIC_KEY=pk-lf-your-public-key
LANGFUSE_SECRET_KEY=sk-lf-your-secret-key
LANGFUSE_HOST=https://cloud.langfuse.com
EOF

Step 4: Verify Connection

// TypeScript verification
import { Langfuse } from "langfuse";

const langfuse = new Langfuse({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY,
  secretKey: process.env.LANGFUSE_SECRET_KEY,
  baseUrl: process.env.LANGFUSE_HOST,
});

// Create a test trace
const trace = langfuse.trace({
  name: "connection-test",
  metadata: { test: true },
});

// Flush to ensure data is sent
await langfuse.flushAsync();
console.log("Langfuse connection successful! Check dashboard for trace.");
# Python verification
from langfuse import Langfuse
import os

langfuse = Langfuse(
    public_key=os.environ.get("LANGFUSE_PUBLIC_KEY"),
    secret_key=os.environ.get("LANGFUSE_SECRET_KEY"),
    host=os.environ.get("LANGFUSE_HOST"),
)

# Create a test trace
trace = langfuse.trace(name="connection-test", metadata={"test": True})

# Flush to ensure data is sent
langfuse.flush()
print("Langfuse connection successful! Check dashboard for trace.")

Output

  • Installed SDK package in node_modules or site-packages
  • Environment variables or .env file with API credentials
  • Successful connection verification trace visible in dashboard

Error Handling

ErrorCauseSolution
Invalid API KeyIncorrect or revoked keyVerify keys in Langfuse dashboard
Connection RefusedWrong host URLCheck LANGFUSE_HOST is correct
Network ErrorFirewall blockingEnsure outbound HTTPS to Langfuse host
Module Not FoundInstallation failedRun
npm install
or
pip install
again
401 UnauthorizedKeys don't match projectEnsure keys are from same project

Examples

TypeScript Initialization with Options

import { Langfuse } from "langfuse";

const langfuse = new Langfuse({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY!,
  secretKey: process.env.LANGFUSE_SECRET_KEY!,
  baseUrl: process.env.LANGFUSE_HOST,
  // Optional configuration
  flushAt: 15,        // Flush after 15 events (default: 15)
  flushInterval: 10000, // Flush every 10 seconds (default: 10000ms)
  requestTimeout: 10000, // Request timeout (default: 10000ms)
  enabled: process.env.NODE_ENV === "production", // Disable in dev
});

// Ensure clean shutdown
process.on("beforeExit", async () => {
  await langfuse.shutdownAsync();
});

Python Initialization with Options

from langfuse import Langfuse
import os

langfuse = Langfuse(
    public_key=os.environ.get("LANGFUSE_PUBLIC_KEY"),
    secret_key=os.environ.get("LANGFUSE_SECRET_KEY"),
    host=os.environ.get("LANGFUSE_HOST"),
    # Optional configuration
    flush_at=15,           # Flush after 15 events
    flush_interval=10.0,   # Flush every 10 seconds
    enabled=os.environ.get("NODE_ENV") == "production",
)

# Register shutdown handler
import atexit
atexit.register(langfuse.flush)

OpenAI Integration (Automatic Tracing)

import { observeOpenAI } from "langfuse";
import OpenAI from "openai";

const openai = observeOpenAI(new OpenAI(), {
  clientInitParams: {
    publicKey: process.env.LANGFUSE_PUBLIC_KEY,
    secretKey: process.env.LANGFUSE_SECRET_KEY,
    baseUrl: process.env.LANGFUSE_HOST,
  },
});

// All OpenAI calls are now automatically traced
const response = await openai.chat.completions.create({
  model: "gpt-4",
  messages: [{ role: "user", content: "Hello!" }],
});

Resources

Next Steps

After successful auth, proceed to

langfuse-hello-world
for your first trace.